MÉTODOS NUMÉRICOS EN INGENIERÍA UAM AZCAPOTZALCO: BAOC (BIG ACADEMIC OPEN COURSE)

ResumenLa demanda creciente de inscripción de alumnos de Licenciatura en las Instituciones de Educación Pública genera la necesidad de nuevas modalidades de conducción del proceso de enseñanza y aprendizaje. En éste trabajo se desarrolla el BAOC (Big Academic Open Course), cursos escolarizados para grupos grandes, su objetivo fue ofrecer una modalidad alternativa para cubrir la demanda creciente de alumnos inscritos en cursos de Ingeniería en la Universidad Autónoma Metropolitana con grupos grandes. Sus características se fundamentan en el b-learning y los MOOC aplicado a cursos escolarizados. Su principal ventaja es que optimiza los recursos físicos y humanos para atender un mayor número de estudiantes, rompiendo el paradigma de tiempo-espacio. Los resultados obtenidos muestran un índice de aprobación medio del 68%, mientras que el índice de retención medio es del 61 %. El 88% de alumnos consideran útil la modalidad y al 76% le gustaría tomar otros cursos en esta modalidad.Palabras Claves: Aprendizaje cooperativo, b-learning, modalidad de conducción del proceso de enseñanza aprendizaje, MOOC.NUMERICAL METHODS IN UAM AZCAPOTZALCO ENGINEERING: BAOC (BIG ACADEMIC OPEN COURSE)AbstractThe growing demand for enrollment of undergraduate students in public education institutions generates the need for new ways of conducting the teaching and learning process. This paper develops the proposal of Semi-faceted School Courses for Large Groups: Big Academic Open Course (BAOC). The objective was to offer an alternative modality to cover the growing demand of students enrolled in Engineering courses at the Autonomous Metropolitan University with large groups. Its characteristics are based on b-learning and the MOOC applied to school courses. Its main advantage is that it optimizes the physical and human resources to attend a greater number of students, breaking the time-space paradigm. The results obtained show an average approval rate of 68%, while the average retention rate is 61%. 88% of students consider the modality useful and 76% would like to take other courses in this modality.Keywords: b-learning, conduction of the teaching-learning process, cooperative learning, MOOC

Desarrollo de un sistema de recomendación de contenidos educativos basado en estilos de aprendizaje aplicado a la Escuela de Ingeniería en Sistemas.

El objetivo del presente trabajo fue desarrollar un sistema recomendador de contenidos educativos basado en estilos de aprendizaje que permita gestionar y recomendar contenidos a estudiantes con la finalidad de mejorar su rendimiento académico. Su desarrollo contempló dos estudios, un estudio preliminar que estableció las preferencias de contenido con respecto a estilos de aprendizaje, y otro estudio para evaluar el rendimiento académico de los estudiantes que emplearon el sistema. Como técnicas de recolección de datos se utilizaron: revisión de documentación, test de estilos de aprendizaje de David Kolb, test para determinar preferencia de contenidos y una evaluación estructurada con preguntas de selección múltiple. La población para los estudios fueron estudiantes de ingeniería en software de la Escuela Superior Politécnica de Chimborazo, siendo la muestra para el primer estudio 128 estudiantes, y para el segundo se tomó a dos grupos de estudiantes determinados como grupo de control y grupo experimental respectivamente, para aplicar y comparar sus resultados al interactuar con el sistema y su contenido. Se realizó el desarrollo del sistema recomendador de contenidos con el lenguaje de programación java, siguiendo la metodología XP, haciendo uso de herramientas y tecnologías como: IDE NetBeans, javascript, Ajax, PrimeFaces y PostgreSQL. Los resultados obtenidos sobre preferencia de formato de contenido en relación al estilo de aprendizaje mostraron que los grupos convergente/asimilador prefieren el formato video, mientras que los grupos divergente/acomodador el formato simulación. La evaluación del rendimiento académico encontró que el grupo experimental obtuvo un promedio de 15.60/20, mientras que el grupo de control 12.74/20. Aplicando la prueba t-student se determinó que existe una diferencia significativa entre las medias de los datos. Se concluye que el uso del sistema recomendador mejoró el rendimiento de los estudiantes en un 14.3%. Se recomienda cargar contenido en diversos formatos para tener más opciones al realizar la recomendación.The objective of this work was to develop an educational content recommender system based on learning styles that allows managing and recommending content to students in order to improve their academic performance. Its development contemplated two studies, a preliminary study that established the preferences of content regarding learning styles, and another study to evaluate the academic performance of the students who utilized the system. As data collection techniques, we utilized the following: documentation review, learning style test of David Kolb, test to determine content preference and a structured evaluation with multiple choice questions. The population for the studies were software engineering students from the Escuela Superior Politécnica de Chimborazo, the sample for the first study were 128 students, and for the second study there were two groups of students named control group and experimental group, respectively to apply and compare their results when interacting with the system and its content. We developed the content recommender system with java language programming following the XP methodology and using tools and technologies such as: NetBeans IDE, javascript, Ajax, PrimeFaces and PostgreSQL. The results obtained related to content format preference in relation to learning style demonstrated that the convergent/assimilator groups prefer the video format, while the divergent/accommodator groups prefer the simulation format. The evaluation of academic performance determined that the experimental group obtained an average of 15.60/20, while the control group obtained 12.74/20. We applied the t-student test and we determined that there is a significant difference between the means of the data. We concluded that the use of the recommender system improved student performance by 14.3%. We suggest uploading content in various formats to have more options when making the recommendation

e-Learning effectiveness in interconnected corporate learning environments

Approaches to workplace learning are continuously evolving to support business objectives but learning and development practitioners are not delivering on their mandate of developing relevant competencies which deliver on strategic objectives. Globally, the proportion of e-Learning to instructor led training is growing and the investment in e-Learning is steadily increasing. Executives expect to see better alignment of e-Learning initiatives and a proven return on investment. In order to earn their place at the executive boardroom, learning and development practitioners need to understand and align their programmes to the context of the business environment in order to positively influence business performance.This research set out to investigate the relationship between the corporate learning environment and e-Learning programme effectiveness using a self-administered questionnaire. The survey was completed by 50 corporate learning and development practitioners. It explored e-Learning programme effectiveness and the configuration of learning environments in relation to a corporate learning environment interconnectedness model proposed in this research. Descriptive statistics, correlation analysis and regression modelling were used to determine the relationship between the environment and e-Learning programme effectiveness. The strongest environmental predictors as well as the current perception of e-Learning programme effectiveness within these environments were also identified.The corporate learning environment was found to be significantly correlated with e-Learning programme effectiveness, specifically in driving higher order benefits of e-Learning programme effectiveness, behaviour change and return on investment. The two strongest predictors of e-Learning programme effectiveness in the corporate learning environment were found to be the definition of clear learning outcomes as well as the provision of opportunities for collaboration in the context of learning. The proposed model of corporate learning environment interconnectedness was also validated and found to be reliable.Dissertation (MBA)--University of Pretoria, 2012.Gordon Institute of Business Science (GIBS)unrestricte

Development and Evaluation of a Sustainable e-Learning Framework for Higher Education Institutions in Malaysia

This thesis focuses on developing and evaluating a sustainable e-learning framework (SeLF) for the higher education institutions in Malaysia. A mixed methods approach was used. Data was collected through surveys from Malaysian universities to assess the characteristics of SeLF. The framework was then evaluated through expert interviews. The thesis highlights SeLF elements and their contribution to the Triple Bottom Line, facilitating sustainable e-learning and its contribution to society, the environment, and the economy